promptukit 0.1.267

Utilities for building question banks and generating exam documents.

PromptuKit

Utilities for building and managing multiple-choice question banks and generating exam PDFs.

Install from PyPI

pip install promptukit

The package is published at https://pypi.org/project/promptukit/. After installing you get the CLI entry points on your PATH:

add-question
extract-question --help
validate-question
question-bank --help

You can also import the library in Python or a Jupyter notebook:

import promptukit as pk
# Top-level helpers: pk.load(path), pk.save(path, data), pk.pick(), pk.confirm()
# Subpackages are available as `pk.exams`, `pk.questions`, and `pk.utils`.

Quick Notebook Walkthrough

Here are short, copy-pasteable examples you can run inside a Jupyter notebook to load a question bank, validate it, and generate a PDF exam.

# 1) Import helpers
import promptukit as pk
from promptukit.questions import validate_question
from promptukit.exams import create_exam

# 2) Load a question bank (path relative to the repository root). If you're
# running outside the repository (for example from an installed package),
# fall back to the packaged sample dataset that ships with `promptukit`.
import os
bank_path = 'content/question_banks/example_sections.json'
if os.path.exists(bank_path):
   data = pk.load(bank_path)
else:
   # load packaged sample included with the installed package
   data = pk.load_resource('question_banks/example_sections.json')

# 3) Inspect the file (section-based vs flat list)
if 'sections' in data:
   print('Sections:', [s.get('title') for s in data['sections']])
   print('First question:', data['sections'][0]['questions'][0])
elif 'questions' in data:
   print('Total questions:', len(data['questions']))
   print('First question:', data['questions'][0])
else:
   print('Unexpected file shape:', type(data))

# 4) Validate programmatically
errors, warnings = validate_question.validate(data)
if errors:
   print('Validation errors:', errors)
else:
   print('Bank valid — warnings:', warnings)

# 5) Generate a PDF exam from the same bank (we already have `data` loaded
# above as a dict, so pass it directly). Note: PDF generation requires
# the `reportlab` package: `pip install reportlab`.
create_exam.build_exam_pdf(data, 'notebooks/output_exam.pdf')

Notes

• If you only want to run the library functions without Poetry activation, you can run modules with python -m promptukit.questions.extract_question or python -m promptukit.exams.create_exam as shown elsewhere in this README.
• Generating PDFs requires reportlab (install with pip install reportlab).

Getting started (Poetry, for development)

1. Install Poetry (if you don't have it):

   pip install --user poetry
   

2. Create the virtual environment and install dependencies:

   poetry install
   

3. Run the CLI tools via Poetry (console scripts / entry points):

   poetry run add-question
   poetry run extract-question --help
   poetry run validate-question
   poetry run question-bank --help
   

Activating the virtualenv

If Poetry is configured to create an in-project virtualenv, it will be placed in a .venv folder at the repository root. Activate that environment from the project root using the command for your shell.

PowerShell (Windows):

.\.venv\Scripts\Activate.ps1

If script execution is blocked, temporarily allow it then activate:

Set-ExecutionPolicy -Scope Process -ExecutionPolicy Bypass
.\.venv\Scripts\Activate.ps1

Command Prompt (cmd.exe):

.\.venv\Scripts\activate.bat

Git Bash / MSYS (Windows):

source .venv/Scripts/activate

macOS / Linux (POSIX):

source .venv/bin/activate

Alternatives (no manual activation required):

# Run a single command inside the virtualenv without activating it
poetry run <cmd>    # e.g. poetry run pytest

Poetry 2.x note:

• The poetry shell command (which previously spawned a new shell) is not installed by default in Poetry 2.0+. You can either use poetry env activate (then evaluate the printed activation command in your shell) or install the shell plugin to restore poetry shell.

Notes

• The package entry points are defined in pyproject.toml under [tool.poetry.scripts] and map console script names to the main() functions in the modules under the promptukit package.

Usage Examples

Quick (Poetry):

poetry run add-question
poetry run extract-question --list-categories
poetry run validate-question
poetry run question-bank extract --help

Extracting data:

# List categories and available fields
poetry run extract-question --list-categories

# Print prompt and answer fields for the 'music' category
poetry run extract-question --file content/question_banks/block-doku-questions.json --category music --fields prompt,answer

# Interactive picker
poetry run extract-question -i

Add questions:

# Interactive add
poetry run add-question

# Batch mode
poetry run add-question --batch new_questions.json content/question_banks/mybank.json

Validate a trivia file:

# Validate the default question bank
poetry run validate-question

# Validate a specific file
poetry run validate-question content/question_banks/block-doku-questions.json

Manage files with question-bank (create/copy/extract):

# Create a new template JSON file
poetry run question-bank create --dest content/question_banks/new.json --categories music,film-and-tv

# Copy an existing file
poetry run question-bank copy --src content/question_banks/block-doku-questions.json --dest content/question_banks/backup.json

# Extract a subset (easy music questions)
poetry run question-bank extract --src content/question_banks/block-doku-questions.json --dest content/question_banks/music_easy.json --categories music --difficulty easy

# Interactive extract
poetry run question-bank extract -i --src content/question_banks/block-doku-questions.json --dest content/question_banks/pick.json

Alternative: run modules with python -m when not using Poetry:

python -m promptukit.questions.add_question
python -m promptukit.questions.extract_question --help
python -m promptukit.questions.question_bank create --dest content/question_banks/new.json

Create exam PDF

The create_exam.py script can generate a printable exam PDF. It accepts an external JSON question bank so you can build exams from your existing content/question_banks/ files.

Usage (from the repository root):

# Use the built-in hard-coded exam
python -m promptukit.exams.create_exam

# Load questions from a JSON bank and write a PDF
python -m promptukit.exams.create_exam -q content/question_banks/block-doku-questions.json -o cven4333_from_json.pdf

# With Poetry (runs the module inside the virtualenv)
poetry run python -m promptukit.exams.create_exam -q content/question_banks/block-doku-questions.json -o cven4333_from_json.pdf

Supported JSON formats

• Top-level sections (preferred):

  {
     "sections": [
        {
           "title": "Section title",
           "questions": [ { "prompt": "...", "choices": ["...", "..."] }, ... ]
        }
     ]
  }
  

• categories is an alias for sections and is also accepted.

• Flat list of questions (top-level array) or top-level object with questions array:

  {
     "questions": [ { "prompt": "...", "choices": ["...", "..."], "category": "Section title" }, ... ]
  }
  

• Question objects support multiple common field names: prompt, q, question, or text for the question text; choices or answers for the answer options; optional category to group flat lists into sections.

• If choices are not already labeled (for example "Oceans" instead of "A) Oceans"), the script will prefix them with A), B), etc. Prompts without a leading number will be auto-numbered sequentially.

Example files

• Example section-based bank: content/question_banks/example_sections.json
• JSON Schema describing accepted layouts: content/question_banks/question_schema.json

Behavior notes

• If no -q/--questions file is provided to the exam generator, the script falls back to the built-in hard-coded 60-question exam and preserves its original 8-section breakdown.
• When you provide a section-based JSON file the PDF's section headings will be taken from each section's title (or name / label if present). When you provide a flat list with category fields, the loader will group questions by category to build sections automatically.

Running Tests

The test suite lives under dev/checks. The file dev/checks/test_question_tool.py contains unit tests that exercise the question-bank helpers and CLI-style interfaces.

Run the tests:

Using Poetry (recommended):

poetry install
poetry run pytest -q

Or run a single file directly:

poetry run pytest dev/checks/test_question_tool.py -q

Notes:

• Tests use pytest's tmp_path fixture and do not modify your repository files.